zscaler_list_toolsets

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, indicating safe read. The description adds that it returns toolsets with specific fields (loaded, count, can_enable), supports substring filters, and warns about can_enable: false being authoritative. No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is concise (5 sentences) and well-structured: purpose, output details, row contents, filter support, and a caution. Every sentence adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a list tool with 3 optional parameters and an output schema, the description fully explains what it does, when to use it, what the output contains, and how to interpret results. It is complete and self-contained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description must compensate. It mentions 'name / description / service substring filters', which maps to the three parameters. While it doesn't detail defaults or exact matching behavior, it adds sufficient context for parameter purpose.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is the 'PRIMARY tool-discovery entry point' and instructs to 'Call this FIRST', distinguishing it from sibling tools which are more specific. It specifies the output: toolsets per resource family per service with examples.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says to call this tool first for any user request needing to find a Zscaler tool. It also provides guidance on interpreting results, e.g., 'Treat can_enable: false as authoritative — do not retry.' This helps the agent decide when to use this tool and how to handle responses.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.